Joint demodulation using a viterbi equalizer having an adaptive total number of states

ABSTRACT

Systems and methods for performing joint demodulation using a Viterbi equalizer having an adaptive total number of states are disclosed. Generally, a method includes joint demodulating a desired signal and one or more interfering signals with a Viterbi equalizer having an adaptive total number of states based on channel impulse response (CIR) coefficients associated with a desired signal and the one or more interfering signals.

CROSS-REFERENCE TO RELATED APPLICATION(S)

The present application is a continuation of U.S. patent applicationSer. No. 12/412,948, filed Mar. 27, 2009, which is a continuation ofU.S. patent application Ser. No. 12/014,348, filed Jan. 15, 2008, (nowU.S. Pat. No. 7,515,660), which is a continuation of U.S. patentapplication Ser. No. 10/737,175 (now U.S. Pat. No. 7,346,130), filedDec. 15, 2003, which is a continuation of U.S. patent application Ser.No. 10/037,300 (now U.S. Pat. No. 6,714,607), filed Dec. 20, 2001, theentirety of each of which is hereby incorporated by reference.

FIELD OF THE INVENTION

The present invention relates to joint demodulation of desired andinterfering signals in Time Division Multiple Access (TDMA) wirelessnetworks for both mobile and fixed applications.

BACKGROUND

In mobile and fixed TDMA networks, frequencies may be reused throughouta given area. Cells are sufficiently separated to insure that co-channelinterference is small relative to the desired signal. However, there arelimits to how often a frequency can be reused since eventually thecarrier-to-interference (C/I) ratio becomes too small for the receiverto properly process a received signal. Since reusing frequencies moreoften implies more channels per cell or sector, and a correspondingincrease in capacity, there is great motivation to develop receiverswhich can operate at low values of C/I (e.g., 4 dB and below).

Many interference cancellation techniques other than joint demodulationrequire at least two antennas on the receive path. Although cellular andpersonal communication system (PCS) base station equipment typicallyemploy multiple antennas on the receive path, mobile terminals andhandset typically employ only a single antenna in light of aestheticsand space constraints.

In conventional receivers employing a single antenna, a number of signalprocessing techniques may be employed to develop an estimate of thedesired signal. A common receiver implementation for wireless networkswith multipath fading uses a Maximum Likelihood Sequence Estimator(MLSE). A detailed description of MLSE can be found in Forney, “MaximumLikelihood sequence estimation of digital sequences in the presence ofintersymbol interference,” IEEE Transactions on Information Theory, Vol.IT-18, pp. 363-378, May 1972.

The MLSE attempts to generate all possible received signals based on allpossible transmitted sequences. The resulting locally-generatedestimates are compared to the signal that is actually received. Thelocally-generated signal that most closely matches the received signalindicates the most likely transmitted sequence. The baseband signal flowassociated with such a receiver and its corresponding transmitter isshown in FIG. 1.

A bit stream b(t) is input to a modulator 10. Based on its inputbit(s)-to-modulator symbol mapping, the modulator 10 produces an outputm(t). The output m(t) is an input to a wireless channel 12. For purposesof this discussion, the wireless channel 12 is assumed to becharacterized as slow, frequency-selective Rayleigh fading. The “slow”description implies that the wireless channel 12 does not changesignificantly over a symbol time of the modulator 10. The“frequency-selective” descriptor implies the existence of multipath, thedelay of which from the main signal is a significant portion of themodulator symbol time (e.g., greater than 25%). The wireless channel 12introduces intersymbol interference (ISI), which typically must becompensated for to achieve satisfactory receiver performance. Thedesired signal after traversing the wireless channel 12 is denoted asC(t).

A separate, co-channel interfering bit stream is denoted by b_(i)(t). Amodulator 14 produces an output m_(i)(t) based on the interfering bitstream b_(i)(t). The output m_(i)(t) is an input to a wireless channel16. A resultant signal of the separate interfering signal path isdenoted as I(t).

Although only one interfering signal is shown, there may be more thanone interferer depending on frequency reuse of the underlying cellularor PCS network. On a TDMA burst-by-burst basis, there may be one or moreinterferers whose respective signal powers contribute significantly tothe total interference power. For simplicity in discussion, only oneinterferer is shown.

A received signal r(t) is equal to a sum of C(t) and I(t). The receivedsignal r(t) is input to a MLSE 20. The MLSE 20 may use a Viterbialgorithm to implement the MLSE functionality. In this case, the MLSE 20may also be referred to as a Viterbi equalizer. A key parameter of theViterbi equalizer is the number of processing states. The number ofprocessing states is typically calculated by M^(L), where M represents amodulator alphabet size, and L represents a memory order of the pathbetween the modulator input and the input to the equalizer. For example,a link employing a binary modulation format, M=2, and a memory order ofL=4 would require a 2⁴=16-state Viterbi equalizer. A particular state inthis example is defined by the four previous modulator symbols, m_(n-1)to m₁₋₄, wherein the time dependence is accounted for in the subscripts.Assuming the modulator alphabet consists of +1 and −1, the states aredefined by the 16 possible combinations of +1 and −1. A possibleprevious modulator output-to-state mapping is shown in FIG. 2. Thisparticular configuration implies that a current received signal r_(n)can be estimated as a function of a current modulator output symbolm_(n) and the four previous modulator output symbols m_(n-1) to m_(n-4)convolved with a channel impulse response (CIR) of the desired signalpath.

In general, the signal estimate for state s can be expressedmathematically as:

$\begin{matrix}{{\hat{r}}_{n} = {\sum\limits_{l = 1}^{L + 1}{{{\hat{h}}_{n}(l)}m_{n - l + 1}^{(s)}}}} & (1)\end{matrix}$

where ĥ_(n)(l) is the I^(th) coefficient of the estimate of the CIR forthe desired signal path at time n, and m^((s)) is the previous modulatorsymbol sequence associated with state s plus the current symbol.

The computation performed for each processing state at each trellisstage within the Viterbi equalizer determines the distance squaredbetween the actual received signal and the locally-generated estimatesdeveloped using the above equation. The equation for distance squaredis:

d ²=|real(r _(n))−real({circumflex over (r)} _(n))²+|imag(r_(n))−imag({circumflex over (r)} _(n))|²  (2)

where real( ) and imag( ) are the real and imaginary parts of therespective quantities.

This calculation is often called a branch metric calculation. The branchmetric calculation is added to the cumulative metric associated witheach state to produce a new set of cumulative metrics as in a standardViterbi algorithm. For binary modulation, there are two new cumulativemetrics generated for each state: one for each of the two possiblemodulator symbols. Thus, for a 16-state equalizer, there are 32 newpaths generated at each trellis stage. At each new state, there are twoincident paths. The path having the minimum cumulative metric isselected as the surviving path. This implies that the selected path is abetter match to the received signal sequence than the non-selected path.The detailed processing associated with a Viterbi equalizer is describedin many references, such as Forney, “The Viterbi Algorithm” Proceedingsof the IEEE, Vol. 61, No. 3, March 1973, pp. 268-278. The end result isthat the Viterbi equalizer produces an estimate of the transmitted bitstream b(t) that was input to the modulator 10. Soft decisions would beemployed if there was a following stage of channel decoding as is thecase for Global System for Mobile Communications (GSM) and ANSI-136 TDMAnetworks. Soft decisions are described in Hagenauer et al., “A ViterbiAlgorithm with Soft-Decision Outputs and its Applications,”CH2682-3/89/0000-1680, 1989, IEEE.

From the above discussion, it is apparent that the complexity of theequalizer is driven by the number of states, since the amount ofprocessing and memory required increases significantly with this keyparameter. Further, since the number of states is seen to growexponentially with the memory order L, it is important to set L to justwhat is needed to properly process the received signal. Too high a valueof L results in a prohibitive amount of processing, while too low avalue of L results in poorer signal estimates and thus poorerperformance.

Conventional receivers estimate the maximum amount of memory that all ofthe possible channels may introduce. The number of states is set basedon this value, provided that it is not prohibitively large so as tosignificantly impact complexity. For example, in the GSM network, themost demanding wireless channel from a memory perspective is HillyTerrain (HT). A detailed description of the HT channel model can befound in the following reference: Digital Cellular TelecommunicationsSystem (Phase 2+); Radio Transmission and Reception, (GSM 05.05 version8.4.0 Release 1999). In the HT channel model, multipath is defined withdelays as great as 20 microseconds. Since a Gaussian minimum shiftkeying (GMSK) symbol time is approximately 3.7 microseconds, L is seento lie between 5 and 6. However, the power in the multipath componentsis typically much less than the main signal, and simulations have shownthat an L of 4 is sufficient. Thus, most existing GSM equipment uses a16-state Viterbi equalizer for the binary GMSK modulation format.

Although joint demodulation concepts have been described in theliterature, one of the primary issues that have limited their usefulnessis implementation complexity.

SUMMARY OF EMBODIMENTS OF THE INVENTION

In at least one embodiment of the invention, a method includes jointlydemodulating a desired signal and one or more interfering signals of areceived signal in response to a carrier-to-interference (C/I) ratioestimate for the received signal being below a threshold level. In atleast one embodiment of the invention, the method includes performingnon joint demodulation of the desired signal in response to the C/Iratio estimate being above the threshold level.

In at least one embodiment of the invention, an apparatus includes achannel estimator configured to estimate a carrier-to-interference (C/I)ratio estimate for a received signal. The apparatus includes ademodulator configured to selectively perform joint demodulation of adesired signal and one or more interfering signals of the receivedsignal based on the C/I ratio estimate and a threshold level.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is pointed out with particularity in the appendedclaims. However, other features are described in the following detaileddescription in conjunction with the accompanying drawings in which:

FIG. 1 is a block diagram illustrating signal paths from a desiredtransmitter and an interfering transmitter to a receiver;

FIG. 2 is a table showing a modulator output-to-state mapping;

FIG. 3 is a flow chart of an embodiment of a method of determining thememory order of the desired and interfering signals;

FIG. 4 is a flow chart of an embodiment of a method of determining thenumber of equalizer states for each burst;

FIG. 5 is a flow chart of an embodiment of a method of adapting betweenconventional processing and joint demodulation processing;

FIG. 6 is a flow chart of an embodiment of a method for compensating fordifferent propagation delays; and

FIG. 7 is a block diagram of an embodiment of a receiver in accordancewith the present invention.

DETAILED DESCRIPTION OF THE DRAWINGS

Embodiments of the present invention address the complexity issue bylimiting the joint processing of the desired signal and the interferingsignal(s) to just what is required based on estimated channelconditions. Instead of locally generating estimates of all possiblesignals based solely on the desired signal, the Viterbi equalizergenerates local estimates of the composite signal consisting of thedesired and interfering signals. Mathematically, this is accomplished bymodifying equation (1) to include the interfering signal. The resultingequation is as follows:

$\begin{matrix}{{\hat{r}}_{n} = {{\sum\limits_{l = 1}^{L + 1}{{{\hat{h}}_{n}(l)}m_{n - l + 1}^{(s)}}} + {\sum\limits_{i = 1}^{L_{i} + 1}{{{\hat{h}}_{i_{n}}(l)}m_{i_{n - l + 1}}^{(s)}}}}} & (3)\end{matrix}$

where the second summation accounts for the interfering signal. The CIRof the interfering signal is different that the desired signal since thetwo signals are assumed to undergo independent fading. In addition, themodulator outputs are different since the signals are representative totwo unique voices and/or data users. These differences are accounted forin equation (3) using the subscript “i” for the respective variables.Also note that the memory order of the interferer, L_(i), is notnecessarily equal to the memory order of the desired signal, L.

For joint demodulation, the number of processing states within theViterbi equalizer is now given by the alphabet size M raised to the(L+L_(i)) power. Thus, the impact of joint demodulation is to increasethe number of states over that typically required to process only thedesired signal. In addition, accounting for both the current desired andinterfering symbols, the number of branch metric calculations per stateis M². For example, in a GSM network with GMSK signals, to represent theinterference to the same level of fidelity as is commonly used today forthe desired signal, the L_(i)=L=4 and the resultant number of states is2⁽⁴⁺⁴⁾=256. A Viterbi equalizer with 256 states is theoreticallyfeasible, but does not lend itself to a practical implementation at thetime of filing this patent application due to the significant increasein processing and memory compared to a 16-state equalizer. This isespecially true of mobile terminal implementations where space andbattery power are limited.

To circumvent this problem, and still achieve most of the gainsassociated with joint demodulation, embodiments of the present inventionadapt the total number of states on a TDMA burst-by-burst basis, andlimit the number of states to what is required based on current channelconditions. The specific number of states for a given burst is dependentupon the power distribution within the CIRs for the desired andinterfering signals for the burst. For example, if the estimated CIR forthe desired and interfering signals shows significant energy for onlythe first three coefficients, then L=L_(i)=2, and a 16-state equalizersuffices. If the desired signal has significant energy in the first fivecoefficients, and the interfering signal has significant energy in onlythe first two coefficients, then L=4, L_(i)=1, and the number of statesis equal to 32. By adapting on a burst-by-burst basis, the instantaneouscomplexity of the equalizer is reduced and preferably minimized. Anadvantage of this approach is that the power consumed is kept low, andpreferably to a minimum, as the receiver processing is matched tochannel conditions.

In addition to the HT channel model, a Typical Urban (TU) channel modeland a Rural Area (RA) channel model are defined for GSM networks. Boththe TU and the RA models are much less demanding from a memoryperspective, with maximum path delays of 5 and 0.5 microseconds,respectively. In addition, channel conditions similar to these twomodels are much more likely to occur than the HT model, which is limitedto mountainous areas of the world. The TU channel model is indicative ofwhat is encountered in a typical city. With a maximum path delay of 5microseconds, a memory order of two suffices for GSM signals. For the RAmodel, there is essentially no memory. Thus, only the current symbol isprocessed from a wireless channel perspective. Note that the use of GMSKmodulation in GSM introduces a memory order of two in the modulationprocess alone, and that the minimum value for L or L_(i) is always tworegardless of the wireless channel. Thus, the joint demodulation with a16-state Viterbi equalizer suffices for the vast majority of mobileconditions encountered. This is important since the vast majority ofexisting implementations are typically limited to 16 states.

For the extreme conditions represented by the HT channel model, thenumber of states can be increased beyond 16, but limited to some maximumvalue to insure a practical implementation. The maximum value isdetermined by trading off performance versus an amount of processingpower and memory available for a given receiver. For example, apractical maximum value for a new GSM receiver at the time of filingthis patent application is about 64 states. One having ordinary skillwill recognize that the maximum value will change as the processingpower and the amount of memory per area increases. Note also that themaximum value for a base station design may be different (e.g.,typically more) than a mobile terminal design since space and power arenot as important for the base station.

FIG. 3 is a flow chart of an embodiment of a method of determining thememory order for either the desired signal or an interfering signal. Asindicated by block 30, the method comprises determining a power in eachCIR coefficient. The CIR is a complex vector consisting of L_(max)+1elements, where L_(max) is the maximum allowable value for the memoryorder. The power in each coefficient is given by the magnitude squaredof the coefficient. For purposes of illustration, an example whereL_(max)=4 is considered. In this example, the power in the five CIRcoefficients at time n are as follows: h_(n)(1)=−9.59 dB, h_(n)(2)=−1.51dB, h_(n)(3)=−9.59 dB, h_(n)(4)=−34.1 dB, and h_(n)(5)=−57.1 dB. Theabove values are representative of a GSM GMSK modulated signal with nofading, but cascaded with a receiver filter before the equalizer with a3 dB bandwidth of approximately 100 kHz.

As indicated by block 32, the method comprises establishing one of theCIR coefficients having a greatest power as a reference coefficient. Thereference coefficient may be the first coefficient in some cases, butmay be another coefficient in other cases. For GMSK signals in theabsence of fading, the reference coefficient is the second coefficient.In the above example, the second element is the reference coefficientsince −1.51 dB is the greatest power value.

As indicated by block 34, the method comprises determining acorresponding relative power of each CIR coefficient in relation to thereference coefficient. If the powers are expressed in a linear scale,each relative power is determined by dividing the power in each of theCIR coefficients by the power in the reference coefficient. If thepowers are expressed in a logarithmic scale such as dB, each relativepower is determined by subtracting the power in the referencecoefficient from the power in the each of the CIR coefficients. Therelative power in the reference coefficient is 1 using a linear scale,and 0 using a logarithmic scale. Continuing with the above example, therelative powers in dB are as follows: h_(n)(1)=−8.08 dB, h_(n)(2)=0 dB,h_(n)(3)=−8.08 dB, h_(n)(4)=−32.59 dB, and h_(n)(5)=−55.59 dB.

As indicated by block 36, the method comprises comparing the relativepowers to a threshold value. In the above example, the threshold valueis selected to be −20 dB. Thus, the first, second and third relativepowers are above the threshold value, and the fourth and fifth relativepowers are below the threshold value.

As indicated by block 40, the method comprises determining a lowestindex value of the CIR coefficients whose relative power is above thethreshold value. In the above example, the lowest index value is 1.

As indicated by block 42, the method comprises determining a highestindex value of the CIR coefficients whose relative power is above thethreshold value. In the above example, the highest index value is 3.

As indicated by block 44, the method comprises determining a span of CIRcoefficients to be used in signal estimation based on the lowest indexvalue and the highest index value. In the above example, the first andthird CIR coefficients define the span of coefficients to be used insignal estimation. Thus, the memory order L is set to two, since thesignal estimate is to be based on the current symbol and the previoustwo symbols.

The above method is applied to both the desired and interfering signalchannel estimates to determine L and L_(i), and ultimately the number ofequalizer states for each burst.

The above method may be extended to consider a plurality of interferingsignals. For N interferers, the number of states required is given by:

s=M ^(L+Σ) ^(k=1) ^(N) ^(L) ^(ik)   (4)

where L_(ik) is the memory order of the k^(th) interferer. For example,for N=2, M=2 and L=L_(i1)=L_(i2)=2, the resulting number of states s isequal to 64. If the memory order is increased to three for each of thesignals, the resulting number of states is equal to 512. Althoughtheoretically sound, using 512 states presently may be impractical toimplement in some applications given finite processing and space. Inaddition, the number of branch metric calculations per state increasesto M^((N+1)).

Although multiple co-channel interferers may exist in a mobile or fixedwireless network, often only one of the interferers is dominant on aTDMA burst-by-burst basis. Thus, all of the detected interfering signalscan be initially processed to determine which one has the most signalpower. In one embodiment, joint demodulation processing is limited justto the interferer with the most signal power. This can be accomplishedin the CIR estimation processing since the power in the CIR coefficientswould be indicative of the power in each of the signals. However, thepresent invention does not preclude processing multiple interferers,particularly when the respective interfering signal powers are of aboutthe same magnitude. For example, if two interferers have nearly equalpowers on the same burst, then processing both is required forsignificant gains in performance. Processing just one of the two wouldtheoretically provide a gain of approximately 3 dB, whereas processingboth could lead to larger gains. The key is to process just what isrequired much in the manner of determining memory order is discussedherein. Thus, an algorithm similar to that in FIG. 3 is contemplatedwhich compares all of the detected interfering signal powers, and thenprocesses those interferers whose relative powers are within somethreshold of the interferer with the most signal power. Processingmultiple interferers is manageable if the number of states required perequation (4) and the resulting complexity is manageable usingstate-of-the-art processing.

The above features, when only one interferer is processed, aresummarized in FIG. 4, which is a flow chart of an embodiment of a methodof determining the number of equalizer states for each burst. Asindicated by block 50, the method comprises estimating the CIRcoefficients for the desired signal channel. As indicated by block 52,the method comprises determining the memory order L for the desiredsignal. The memory order L is determined by applying the method of FIG.3 to the CIR coefficients for the desired signal channel. As indicatedby block 54, the method comprises estimating the CIR coefficients foreach interfering signal channel that is detected. As indicated by block56, the method comprises determining which of the detected interferingsignals has the greatest power. As indicated by block 60, the methodcomprises determining the memory order L_(i) for the interfering signalhaving the greatest power. The memory order L_(i) is determined byapplying the method of FIG. 3 to the channel estimates for theinterfering signal having the greatest power. It is straightforward toexpand FIG. 4 to include multiple interferers.

Various known solutions exist for estimating the CIRs for the desiredand interfering signals in TDMA wireless networks. For example, in GSMand ANSI-136, training sequences included in the burst format can beused for estimating the CIR. In GSM, there are a number of uniquetraining sequence codes (TSCs) which are inserted in the middle of atypical GSM burst. For most anticipated vehicle speeds, the CIRestimated from the TSC is essentially constant over the entire burstwhich is approximately 0.577 ms in length. Thus, the CIR need only becalculated once in GSM networks. This is not typically the case forANSI-136 networks where the burst length is 6.67 ms, within which timethe channel can significantly change. In this case, the CIR based on thetraining sequence (which is called a “sync” word in ANSI-136) isinterpolated over the burst.

To distinguish the desired signal from the interfering signal, theinterfering signal should have a different TSC or sync word than thedesired signal. Use of the herein-described techniques in a GSM orANSI-136 network is promoted by proper TSC and sync word planningthroughout a service area.

FIG. 5 is a flow chart of an embodiment of a method of adapting betweenconventional processing and joint demodulation processing. As indicatedby block 70, the method comprises estimating the C/I on a burst-by-burstbasis. The previously-described CIR estimation process can be used toprovide the C/I estimate. As indicated by block 72, the method comprisescomparing the C/I to a threshold. If the C/I is less than the threshold,an act of performing joint demodulation processing is performed asindicated by block 74. If the C/I is greater than or equal to thethreshold, an act of performing conventional processing (i.e., non jointdemodulation) is performed as indicated by block 76. There is no needfor joint demodulation when the contribution to the received signal dueto the interferer is negligible. Suitable, and optionally optimum,values of the threshold can be determined through a combination ofsimulations, lab testing and field trials.

Another aspect of embodiments of the present invention is its capabilityfor use in both synchronous and asynchronous operation. By synchronousoperation, it is meant that each burst emanating from a base station issynchronized with every other base station in the service area. Byasynchronous operation, it is meant that the bursts are notsynchronized.

Due to possible different propagation delays between the desired signaland the interfering signal, the desired signal and interfering signalmay not be synchronized at the modulator symbol level even undersynchronous operation. In other words, synchronous operation does notguarantee synchronized signals. For example, in a GSM downlink, adifference in propagation delay of about 3.33 microseconds results ifthe interfering base station is 1 km further away from the mobilestation than the desired base station. This particular value of delay issignificant with respect to a GSM symbol time of 3.69 microseconds, thusresulting in signals which are not synchronized.

FIG. 6 is a flow chart of an embodiment of a method for compensating fordifferent propagation delays. As indicated by block 90, the methodcomprises determining a first cross-correlation function between thereceived signal and an embedded training sequence of the desired signal.The cross-correlation function can be used to provide an estimate of theCIR. As indicated by block 92, the method comprises determining a firsttime value of a peak in the first cross-correlation function. The timeoccurrence of the peak provides a time reference for the receiver.

As indicated by block 94, the method comprises determining at least onesecond cross-correlation function between the received signal and thetraining sequences of each of the possible interferers. This act isperformed to determine the delay between the desired signal and thepossible interferers. The cross-correlation function(s) can be used toprovide estimates of the CIRs of the possible interferers. Theinterfering CIR with the greatest power indicates the most dominantinterferer. Others of the possible inteferers whose signal power iswithin some threshold difference of the most dominant interfering signalmay also be considered as dominant interferers.

As indicated by block 96, the method comprises determining a second timevalue of a peak in the second cross-correlation function for thedominant interferer. The time occurrence of the peak determines thepropagation delay of the dominant interferer.

As indicated by block 98, the method comprises determining a timedifference t_(d) between the first time value and the second time value(i.e., between the time occurrences of the desired and interferercorrelation peaks). As indicated by block 99, the time difference isused in the estimation of the interfering signal's CIR, and insures thatthe estimated signal is a faithful representation of the actual receivedsignal.

For purposes of illustration and example, consider a GSM networkemploying GMSK modulation. For proper signal representation, thereceiver samples the received signal at some multiple of the modulatorsymbol rate. For the GSM GMSK waveform, a sampling rate of four timesthe symbol rate has been found to be a good compromise between signalfidelity and processing required. Thus, in the CIR estimation process,the correlation peak can be resolved to a quarter of a symbol time,which is equal to approximately 0.923 microseconds. This time translatesinto a propagation distance of about 277 meters. Thus, the difference inpropagation time between the desired signal and the interfering signalis in units of quarter symbol periods. Note that although thecorrelation peak is resolved to within a quarter of a symbol, the actualCIR coefficients are typically determined from a downsampled (at thesymbol rate) version of the received signal to reduce the processingload. Thus, the CIR coefficient spacing is a symbol time.

Through simulations of the GMSK waveform, it has been found that thetime difference determines the time shift required in the selection ofthe coefficients to be used for the interfering CIR. In oneimplementation of the CIR estimator, the training sequence of thedesired signal is first correlated with the entire GSM burst. Thecoefficients for the desired signal CIR are determined by finding theL+1 contiguous coefficients with the most signal power. To find theinterfering signal's CIR, the entire burst is then correlated with thedominant interferer's training sequence, however the actual coefficientsselected are determined by the time difference t_(d).

One approach to determining CIR coefficients is as follows. In thefollowing description, the time difference t_(d) is represented inintegral units of quarter symbols. If 2≧t_(d)≧0, then the interferer CIRcoefficients h_(i) are considered to occur at the same time as thedesired signal CIR coefficients h. If 6≧t_(d)≧3, then the h_(i)locations are offset delayed by one sample relative to h. If 10≧t_(d)≧7,then the h_(i) locations are offset delayed by two samples relative toh. The process continues for increasing values of t_(d), where the h_(i)locations are offset delayed by int((t_(d)+1)/4) samples relative to h,and where int( ) is the integer function.

If an interferer is closer in location than the desired signal, thet_(d) values are negative. If 0≧t_(d)≧−2, then the h_(i) locations occurat the same time as the h locations. If −3≧t_(d)≧−6, then the h_(i)locations are one sample ahead of the h locations. If −7≧t_(d)≧−10, thenthe h_(i) locations are two samples ahead of the h locations. Theprocess continues for decreasing values of t_(d), where the h_(i)locations are ahead of the h locations by int((1−t_(d))/4) samples.

Embodiments of the present invention are able to process bothsynchronous and asynchronous systems, since both possibly require theprocessing of non-synchronized signals. A synchronous system ispreferred since the average time difference is apt to be a much smallervalue than would be determined in an asynchronous system. This smallervalue helps narrow the search for the interferer's correlation peak, andmay translate into a quicker and more reliable channel estimationprocess.

To draw together the teachings herein, FIG. 7 shows a block diagram ofan embodiment of a receiver in accordance with the present invention.The blocks in FIG. 7 are functional blocks which may be implemented byone or more components. Optionally, the functionality of one or moreblocks is provided by a processor of a computer system. The processormay be directed by a computer-usable medium having computer program codeembodied thereon to perform any of the acts described herein.

The receiver comprises a channel estimator 100 which performs theherein-disclosed CIR estimation acts based on a received signal 102. Thechannel estimator 100 also includes processing which performs theherein-disclosed cross-correlation acts based on the received signal102. An integral cross-correlator 104 determines the cross correlationfunctions. An integral cross-correlator processor 106 processes theresulting cross correlation functions. The channel estimator 100 alsoincludes processing to synchronize the receiver to the desired signal.An interfering signal selector 110 determines the dominant interferingsignal(s). A coefficient processor 112 trims the CIR coefficientsassociated with the desired signal and the dominant interferingsignal(s), thereby producing respective memory orders which dictate anadaptive number of states. A demodulator 114 jointly demodulates thedesired signal and the dominant interfering signal(s) with a Viterbiequalizer having the adaptive total number of states.

Thus, there have been described herein methods and systems to perform ajoint demodulation of desired and interfering signals having an adaptivetotal number of Viterbi equalizer states based on the power distributionof the respective CIR estimates. Beneficially, the Viterbi equalizer ismatched to the current channel conditions. In this way, the processingand battery power are reduced, and preferably minimized, on aburst-by-burst basis.

In contrast, conventional joint demodulators fix the number of statesbased on the worst-case channel conditions (e.g., mountainousconditions), which typically do not occur often. Thus, the processingpower is over provisioned in conventional systems to take care ofextreme cases.

By allocating processing power on an as-needed basis, freed-upprocessing power may be allocated to perform joint demodulation of thedesired signal and one or more dominant interferers.

Any performance gain which results from the herein-disclosed teachingsmay be applied to any combination of: (a) tighter frequency reuse forboth voice and data supporting higher spectral efficiency provided thereis balance on the uplink, (b) higher data throughputs and higher voicequality in existing reuse patterns, and (c) potential deployment of theGSM Adaptive Multi-Rate (AMR) vocoder operating in the Half-Rate (HR)mode, which gives automatic doubling in voice capacity over the GSMFull-Rate (FR) or the enhance FR (EFR). In addition, embodiments of thepresent invention can be used on an uplink for base stations that onlyhave room for one antenna.

It will be apparent to those skilled in the art that the disclosedinventions may be modified in numerous ways and may assume manyembodiments other than the preferred forms specifically set out anddescribed herein. For example, acts described with reference to FIGS. 3to 6 may be performed either in a different order or in parallel.

Accordingly, it is intended by the appended claims to cover allmodifications which fall within the true spirit and scope of the presentinvention.

What is claimed is:
 1. A method comprising: jointly demodulating adesired signal and one or more interfering signals of a received signalin response to a carrier-to-interference (C/I) ratio estimate for thereceived signal being below a threshold level.
 2. The method, as recitedin claim 1, further comprising: performing non joint demodulation of thedesired signal in response to the C/I ratio estimate being above thethreshold level.
 3. The method, as recited in claim 1, wherein thereceived signal is a time division multiple access (TDMA) signal and themethod further comprises: estimating the C/I ratio on a burst-by-burstbasis.
 4. The method, as recited in claim 1, wherein the jointlydemodulating uses a Viterbi equalizer having an adaptive total number ofstates based on first channel impulse response (CIR) coefficientsassociated with the desired signal and second CIR coefficientsassociated with the one or more interfering signals.
 5. The method, asrecited in claim 4, further comprising: determining the second CIRcoefficients based on a first cross-correlation function between thereceived signal and a training sequence of an interfering signal of theone or more interfering signals; and determining the first CIRcoefficients based on a second cross-correlation function between thereceived signal and a training sequence of the interfering signal. 6.The method, as recited in claim 5, further comprising: determining atime difference between a time value of a peak in the firstcross-correlation function and a time value of a peak in the secondcross-correlation function, wherein determining the second CIRcoefficients is further based on the time difference.
 7. The method ofclaim 4, wherein the one or more interfering signals comprises at leastone dominant interfering signal and each of the at least one dominantinterfering signal has a signal power which is within a thresholddifference of the dominant interfering signal having a greatest power.8. The method of claim 7, further comprising: detecting the one or moreinterfering signals.
 9. The method of claim 7, further comprising:determining the at least one dominant interfering signal of the one ormore interfering signals.
 10. An apparatus comprising: a channelestimator configured to estimate a carrier-to-interference (C/I) ratioestimate for a received signal; and a demodulator configured toselectively perform joint demodulation of a desired signal and one ormore interfering signals of the received signal based on the C/I ratioestimate and a threshold level.
 11. The apparatus of claim 9, whereinthe demodulator is configured to perform non joint demodulation of thedesired signal in response to the C/I ratio estimate being above thethreshold level.
 12. The apparatus of claim 9, wherein the receivedsignal is a time division multiple access (TDMA) signal and the channelestimator is configured to estimate the C/I ratio on a burst-by-burstbasis.
 13. The apparatus of claim 9, wherein the demodulator isconfigured to perform the joint demodulation of the desired signal inresponse to the C/I ratio estimate being below the threshold level. 14.The apparatus of claim 13, wherein the joint demodulation of the desiredsignal and the one or more interfering signals uses a Viterbi equalizerhaving an adaptive total number of states based on first channel impulseresponse (CIR) coefficients associated with the desired signal andsecond CIR coefficients associated with the one or more interferingsignals.
 15. The apparatus of claim 13, wherein the one or moreinterfering signals comprises at least one dominant interfering signaland each of the at least one dominant interfering signal has a signalpower which is within a threshold difference of the dominant interferingsignal having a greatest power.
 16. The apparatus of claim 15, whereinthe demodulator is further configured to determine the at least onedominant interfering signal of the one or more interfering signals. 17.The apparatus of claim 14, wherein the channel estimator is furtherconfigured to determine the first CIR coefficients associated with aninterfering signal of one or more interfering signals and configured todetermine the second CIR coefficients associated with a desired signal.18. The apparatus of claim 17, wherein the second CIR coefficients arebased on a first cross-correlation function between the received signaland a training sequence of an interfering signal of the one or moreinterfering signals, and wherein the first CIR coefficients are based ona second cross-correlation function between the received signal and atraining sequence of the interfering signal.
 19. The apparatus of claim17, wherein the second CIR coefficients are based on a time differencebetween a time value of a peak in the first cross-correlation functionand a time value of a peak in the second cross-correlation function. 20.A non-transitory computer-readable storage medium comprising a set ofinstructions to direct a processor to perform acts of: jointlydemodulating a desired signal and one or more interfering signals of areceived signal in response to a carrier-to-interference (C/I) ratioestimate for the received signal being below a threshold level; andperforming non joint demodulation of the desired signal in response tothe C/I ratio estimate being above the threshold level.